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Accounting and CFO firm automation guide 2023

Most accounting and CFO firms still have many manual, repetitive, and mundane tasks in most of their workflows such as accounts payable(AP), accounts receivable, reconciliation, payroll, etc.

In 2023, these companies can leverage technology such as AI and RPA to automate most of these tasks and increase their productivity at least by 3X. The transformation has already started a few years ago and by now, the front runners have automated some of their processes fully or partially. The year 2023 is crucial for all accounting and CFOs to get there where they need to be.

What processes can you automate in accounting and CFO firms?

Unlike finance departments of mid or large corporations, accounting firms deal with many smaller businesses and each business can have their own accounting software and process and in most cases, CPAs want to streamline and standardize processes for all of their clients for easy execution. Almost all the processes including accounts payable, accounts receivable, reconciliation, payroll, etc. can be automated through AI and RPA.

Invoices Processing and Accounts Payable (AP) Automation in Accounting and CFO Firms

Accounts payable (AP) is a critical and often complex process in CPA and CFO firms. However, advancements in Artificial Intelligence (AI) and Robotic Process Automation (RPA) have paved the way for automating AP tasks, enabling increased efficiency and accuracy. This guide aims to provide CPA and CFO firms with insights into automating invoice processing and AP workflow using AI and RPA technologies.

Step 1: Invoice Sourcing Invoices typically arrive via email from various clients. To streamline the process, the first step is to identify the client sending the invoices and collect them for further processing. A bot or automation script can be set up to track the “from email” ID and automatically assign invoices to the respective clients. This helps organize incoming invoices efficiently.

Step 2: Data Extraction with AI: To extract relevant data from invoices, an AI model is utilized. Pre-trained AI models are available, which can accurately extract the required data points for payment processing, such as vendor information, invoice number, dates, and amounts. In cases where additional data extraction is needed, firms have the option to train the AI model using their own invoices. It is important to note that the accuracy of the AI model improves with more data, allowing for more precise extraction. Some companies also offer pre-trained AI models through APIs, simplifying the integration process.

Step 3: Data Validation: Before bringing the extracted data into the existing system, it is crucial to validate the accuracy of the data. While AI models excel at data extraction, a human validator is required to ensure the extracted information aligns with the original invoice. Document AI platforms often provide data validation interfaces where validators can compare the original document with the captured data side-by-side, enabling efficient and accurate validation.

Step 4: Integration with Accounting Systems Once the data has been validated, it needs to be populated into the existing accounting system. Most document AI platforms offer API and webhook integration capabilities, allowing for seamless data transfer. By leveraging the API or webhook, the captured invoice data can be easily integrated into the accounting system. This automated integration eliminates the need for manual data entry, reduces errors, and ensures a streamlined AP process.

Benefits of AP Automation for CPA and CFO Firms

Time Savings: Automation significantly reduces the time spent on manual data entry and invoice processing, enabling staff to focus on higher-value tasks.
Increased Accuracy: AI-powered data extraction minimizes errors by extracting data precisely, reducing the risk of human mistakes.
Cost Efficiency: AP automation reduces the need for extensive manual labor, leading to cost savings in terms of staffing requirements.
Improved Compliance: Automation ensures consistency in data extraction and validation, enhancing compliance with regulatory standards and internal policies.
Enhanced Decision-Making: With streamlined AP processes, firms have access to accurate and real-time financial data, enabling informed decision-making for financial planning and forecasting.

By embracing AI and RPA technologies, CPA and CFO firms can significantly improve their AP processes, reduce manual effort, and enhance accuracy. Automation of invoice sourcing, data extraction, validation, and integration with accounting systems streamlines the AP workflow, providing time and cost savings while ensuring compliance and facilitating better financial decision-making. Implementing AP automation empowers CPA and CFO firms to focus on strategic activities, driving greater efficiency and productivity within their organizations.

Streamlining Receipt Processing: Harnessing OCR and AI Technology for Efficient Data Capture:

Receipt processing can often be a time-consuming and tedious task for finance. Many firms face the challenge of handling thousands of receipts sent via email, ranging from scanned PDFs with multiple receipts to simple snapshots taken on mobile devices. To alleviate this burden, advancements in Optical Character Recognition (OCR) and Artificial Intelligence (AI) technologies have revolutionized the way we identify, extract, and manage data from receipts.

The Role of OCR and AI in receipts processing

AI along with the OCR technology has emerged as a game-changer in the realm of receipt processing. It leverages sophisticated algorithms to convert scanned or photographed text into machine-readable data. This means that even if a client sends a PDF with multiple receipts or a picture of a receipt, AI can accurately identify the text and extract relevant information such as vendor details, transaction dates, and amounts. AI can also capture data from receipts that it has never seen before. Unlike the traditional OCR, AI follows the context-based approach instead of the template-based approach.

Streamlining workflow through existing system integration

Once receipt data is captured through OCR and AI, the next step is to seamlessly integrate it into accounting software or other relevant applications. This is where APIs and webhooks come into play. Most of the document AI platforms provide APIs and webhooks. APIs act as bridges, allowing different systems to communicate and exchange data. Webhooks provide real-time notifications, ensuring that data updates are automatically reflected in the target software. By leveraging these integration capabilities, receipt data can be efficiently transferred to popular accounting software like QuickBooks or other relevant platforms, eliminating the need for manual data entry and reducing the risk of human error.

Streamlining Credit Card Statement Data Capture and Processing

For accounting firms, efficiently managing credit card statement data is crucial for accurate financial reporting and bookkeeping. However, the process of capturing and processing data from various credit card statements can be time-consuming and prone to errors. However, accounting firms can streamline this workflow by leveraging technology and automated solutions, ultimately improving efficiency and ensuring data integrity when integrating credit card transactions into accounting software.

Step 1: Automating the collection of Credit Card Statements is the first step in the process. These statements may be received in various formats, such as PDFs, electronic statements, or physical copies. Creating a standardized process for receiving and organizing these statements will help streamline the subsequent steps.

Step 2: AI and OCR for Data Extraction: To extract data from credit card statements, accounting firms can employ AI and OCR technology. OCR converts scanned or photographed text into machine-readable data. OCR software can intelligently recognize and capture relevant information from credit card statements, such as transaction dates, descriptions, amounts, and vendor details. This automated data extraction significantly reduces the need for manual data entry and minimizes human error.

Step 3: Data Validation and Cleaning: After the data is extracted through OCR, it is essential to validate and clean the captured information. Automated data validation algorithms can be applied to check for accuracy, completeness, and consistency. These algorithms can detect potential discrepancies or anomalies in the extracted data, allowing for timely corrections and ensuring data integrity.

Step 4: Mapping to Accounting Software: Once the credit card statement data is validated and cleaned, it needs to be mapped to the appropriate accounts in the accounting software. CPA firms can create mappings that associate specific transaction types with the corresponding general ledger accounts. Mapping automation tools can streamline this process by assigning transactions to predefined categories, reducing manual effort, and minimizing the chance of errors.

Step 5: Integration with Accounting Software: The final step is to integrate the processed credit card statement data into the accounting software. Most accounting software solutions provide APIs or import functionality that allow for seamless integration. Data can be directly imported into the software, ensuring that credit card transactions are accurately recorded and reconciled with other financial data.

Benefits of Automated Credit Card Statement Processing:

Time Efficiency: Automation reduces the time spent on manual data entry and processing, allowing CPA firms to focus on higher-value tasks such as analysis and advisory services.
Accuracy and Data Integrity: OCR technology and automated validation processes minimize errors and ensure the accuracy and integrity of credit card statement data.
Streamlined Reconciliation: By integrating credit card transactions into accounting software, the reconciliation process becomes more efficient and accurate.
Enhanced Reporting: Automated processing provides timely and accurate financial data, enabling CPA firms to generate insightful reports for clients, management, and regulatory purposes.
Scalability and Consistency: With automation, CPA firms can handle a higher volume of credit card statements consistently, maintaining data quality and meeting client demands.

Automating the capture and processing of credit card statement data is a game-changer for accounting firms. Implementing automated solutions for credit card statement processing allows accounting firms to provide more efficient and reliable financial services to their clients, while also freeing up time for strategic decision-making and value-added activities.

Automating Accounts Receivable Processes for Accounting Firms: Streamlining Efficiency and Boosting Productivity

Manual handling of Accounts Receivable (AR) tasks is time-consuming, error-prone, and hinder overall productivity. Using the latest AI technology and RPA, we can automate most of the tasks in AR.

What tasks can be automated in AR?

Invoice Generation and Delivery: RPA bots can be used in accounting firms to generate and send invoices for their clients automatically. This includes collecting data from other sources and adding relevant billing details, and delivering them via email or electronic platforms. Automation ensures invoices are promptly generated, reducing delays in payment processing.
Payment Reminders and Collections: With RPA you can automate the entire collection and follow up processes. Automation can handle scheduling and sending personalized payment reminders to clients. thereby improving cash flow and reducing the burden on account managers.
Payment Reconciliation: Matching and reconciling payments received with outstanding invoices can be complex. Automation tools can compare payment information with invoiced amounts, cross-referencing them to identify discrepancies and ensure accurate reconciliation. This reduces manual effort and minimizes the risk of errors. If you have a large customer base with smaller payments, bot can do the reconciliation efficiently and accurately.
Data Entry and Updating: Automating data entry eliminates the need for manual input of payment details into accounting systems. Technologies such as OCR can extract relevant payment information from remittance advice or bank statements, credit card statements automatically populating the data in the accounting software. This streamlines the process, enhances accuracy, and saves time.

Technologies used for automation:

Robotic Process Automation (RPA): RPA can mimic human actions to perform repetitive tasks, such as invoice generation, payment reminders, and data entry. RPA bots can be programmed to follow predefined rules and workflows, reducing manual intervention and speeding up processes.
Artificial Intelligence (AI): AI technologies, including machine learning algorithms, can be utilized for tasks such as invoice matching, identifying payment patterns, and predicting payment delays. AI helps automate decision-making processes by analyzing historical data and patterns, leading to more accurate and proactive AR management.
Integration with Accounting Software: Seamless integration between automation tools and accounting software, such as QuickBooks or Xero, is crucial for efficient data transfer. Application Programming Interfaces (APIs) enable the exchange of information, allowing automated systems to directly update account balances, payment statuses, and other relevant data in real-time.

Benefits of AR automation for accounting firms:

Time and Cost Savings: Automation significantly reduces manual effort, allowing accountants to focus on higher-value tasks. It eliminates repetitive data entry, decreases administrative costs, and improves overall productivity.
Improved Cash Flow and Faster Payments: Automation streamlines the AR process, facilitating prompt invoice generation, payment reminders, and collections. This improves cash flow, reduces outstanding balances, and accelerates payment cycles.
Enhanced Accuracy and Reduced Errors: Automation minimizes human errors associated with manual data entry, ensuring accurate and reliable financial records. This improves the integrity of financial data and reduces the need for error correction.
Increased Efficiency and Scalability: Automated AR processes enable accounting firms to handle higher volumes of transactions efficiently, eliminating the constraints of manual processing. This scalability ensures firms can cater to growing client needs without compromising quality.
Data-Driven Decision Making: AR automation provides real-time visibility into payment statuses, aging reports, and customer behaviors. This data empowers accounting firms to make informed decisions, identify trends, and develop strategies to optimize cash flow management.

Implementing AR automation in accounting firms brings transformative benefits. Firms can achieve increased efficiency, improved accuracy, and enhanced cash flow management. Leveraging technologies like RPA, AI, and seamless integration with accounting software, accounting firms can streamline their AR processes, reduce manual effort, and allocate more time to strategic financial management.

Reconciliation processes automation for accounting and CFO firms

Reconciliation has long been regarded as one of the most time-consuming and arduous tasks for financial institutions. Financial professionals must meticulously review each transaction in bank and credit card statements, compare them with previous records, and allocate them to the appropriate categories. This process becomes particularly daunting when organizations use QBD (Quickbook Desktop), which further complicates the process.

Fortunately, in 2023, financial institutions can leverage the power of RPA and Document AI technology to tackle these challenges head-on.

Tasks that Document AI and RPA can automate in the reconciliation process:

Data Extraction: Document AI technology can automatically extract data from various documents, such as bank statements, credit card statements, and receipts. It eliminates the need for manual data entry, reducing the chances of errors and speeding up the reconciliation process.
Accounting system integration: All the captured transactions need to be populated to the existing accounting system. RPA and other interaction technologies can do this efficiently. For Quickbook Desktop RPA bot can be used for integration.
Categorization of transactions: RPA bot can look into the historical transactions to find out the right category for the new traction and categorize the new transactions accordingly.
Data cleaning: There are occasions when employees make some personal purchases. These transactions can also be detected and eliminated if needed.
Reconciliation Report Generation: Document AI and RPA can automatically generate reconciliation reports with accurate data, saving significant time for accounting and CFO professionals. These reports can provide an overview of discrepancies, outstanding items, and help track the progress of the reconciliation process.
Account Reconciliation: RPA can automate the matching and reconciliation of various accounts, such as bank accounts, general ledgers, and sub-ledgers. By comparing large volumes of data accurately and efficiently, automation reduces the risk of errors and enables faster resolution of discrepancies.

Benefits of Automation in Reconciliation Processes:

Increased Efficiency: By automating time-consuming manual tasks, accounting and CFO firms can significantly improve the efficiency of the reconciliation process. Employees can focus on higher-value activities that require human judgment and expertise, such as data analysis and decision-making.

Improved Accuracy: Automation reduces the chances of human error associated with manual data entry and matching. With Document AI and RPA, the reconciliation process becomes more accurate, minimizing the risk of financial discrepancies and compliance issues.
Cost Savings: Automation eliminates the need for additional staff to perform repetitive reconciliation tasks. By reducing labor costs and increasing productivity, accounting and CFO firms can achieve substantial cost savings.
Enhanced Compliance: Automated reconciliation processes ensure greater compliance with regulatory requirements. By reducing errors and improving accuracy, firms can minimize the risk of financial penalties, audits, and reputational damage.
Real-Time Insights: Automation provides real-time visibility into the reconciliation process, allowing firms to identify issues promptly and take immediate corrective actions. This enables proactive decision-making and enhances financial control and risk management.
Scalability: As businesses grow, the volume of financial transactions and reconciliation tasks increases. Automation allows firms to scale their operations efficiently without compromising accuracy or speed, ensuring that reconciliation processes keep pace with organizational growth.

Incorporating document AI and RPA into accounting processes offers tremendous benefits for accounting and CFO firms. By automating data extraction, accounts payable (AP), accounts receivable, reconciliation, report generation, firms can achieve greater efficiency, accuracy, cost savings, compliance, and real-time insights. Embracing these technologies empowers professionals to focus on value-added activities, ultimately driving better financial control, decision-making, and overall business success.